110 results about "Balance energy" patented technology

The invention discloses a multi-level energy management system based on multi-dimensional data, and relates to the technical field of energy intelligent management, and the system comprises a multi-source data collection module which collects power utilization, environment and equipment state data in real time; the data fusion processing module is used for processing abnormal values through an algorithm and fusing multi-scale data features; the energy state evaluation module is used for realizing equipment state evaluation and early warning by using a fusion algorithm and a prediction model; the multi-level energy scheduling module adopts an optimization algorithm to balance the energy cost, the production efficiency and the carbon emission, and dynamically adjusts the strategy; the energy performance analysis module is used for developing an analysis tool and an evaluation model; and the decision support module is used for configuring an expert knowledge base and developing a fault diagnosis system and a knowledge graph. Through multi-dimensional data acquisition and multi-level management, the energy data error is greatly reduced, the comprehensive energy cost and carbon emission are remarkably reduced, the cost of participating in enterprise operation is reduced, and the accuracy, safety and sustainability of energy management are improved.

The invention relates to an intelligent analysis method for energy consumption of industrial solid waste treatment, which comprises the following steps of: constructing a layered digital twinborn model for mapping a physical structure, a process flow and an energy consumption relationship through multi-point multi-dimensional data fusion acquisition and data cleaning, synchronization and standardized preprocessing; the model is used for feature coupling extraction and anomaly detection, spatial positioning and analysis of energy consumption anomaly are realized, multi-scene deduction and parameter optimization are performed through a digital twin sandbox, influence paths and anomaly factors are accurately identified, and optimal intervention suggestions giving consideration to energy conservation, productivity and process stability are automatically given. According to the scheme, the real-time performance and accuracy of energy consumption abnormity diagnosis of the production line are improved.

The invention relates to the technical field of Bluetooth control, and discloses a signal receiving sensitivity optimization method and system for a low-power-consumption dual-mode Bluetooth chip, and the method comprises the steps: monitoring a signal receiving environment of the Bluetooth chip, obtaining the characteristics of the signal environment, switching the Bluetooth chip to a precise mode or a low-consumption mode according to the characteristics of the signal environment, and achieving the optimization of the signal receiving sensitivity of the low-power-consumption dual-mode Bluetooth chip. In a precise mode or a low consumption mode, according to a preset signal parameter adjustment scheme, radio frequency communication and demodulator parameters are optimized in real time to ensure that the signal receiving sensitivity meets the standard, the signal effect of the Bluetooth chip is synchronously monitored, the signal parameter scheme is adjusted and optimized according to the monitoring result, and the radio frequency communication and demodulator parameters are continuously adjusted. By intelligently switching the working modes and dynamically adjusting the parameters, the receiving sensitivity of the Bluetooth chip in different signal environments is optimized, the Bluetooth device is ensured to keep stable communication in various environments through real-time synchronous monitoring and adjustment, and the problem that the Bluetooth chip is difficult to balance energy consumption and communication quality in the prior art is solved.

The invention discloses a new energy automobile high-voltage connector thermal management system and an optimization control method, and relates to the technical field of connecting piece thermal management. The multi-dimensional temperature sensing module is used for acquiring and fusing data by using a thermocouple, an infrared sensor and the like; the combined type heat dissipation execution module adopts a bionic liquid cooling plate, a nano coating fin and a semiconductor chilling plate to dissipate heat; the intelligent heat management control module is used for adjusting heat dissipation by means of an MPC algorithm and fuzzy PID; the fault diagnosis and safety protection module can give an alarm, cut off power and guarantee the reliability of the sensor; and the data interaction and optimization module is used for realizing data interaction and strategy remote optimization. Through multi-module cooperation and intelligent control, the working temperature of the connector is reduced, the heat dissipation efficiency and the control precision are improved, the response time is shortened, and the energy consumption and the service life are balanced; and meanwhile, the fault diagnosis capability is enhanced, the maintenance frequency is reduced, strategy optimization is realized by means of a digital technology, and safe and efficient operation of the high-voltage connector is guaranteed.

The invention belongs to the technical field of industrial automation, and discloses a multi-target energy consumption analysis and dynamic optimization system based on deep reinforcement learning. The objective of the invention is to solve the problems of state characterization lagging and insufficient optimization decision of industrial equipment under instantaneous load change. The system accurately characterizes the equipment state change rule by constructing a dynamic state transfer chain; a response priority is scientifically determined by analyzing a state transition path and a load change trend; in combination with dynamic decision logic of deep reinforcement learning, equipment operation parameters are optimized; the energy consumption, the response speed and the stability are balanced through a multi-objective optimization strategy; and finally, high-efficiency operation is realized through real-time regulation and control. According to the invention, the adaptability of the system to complex working conditions, the scientificity of response and the energy utilization efficiency are improved, and the production cost is reduced.

The invention is suitable for the field of intelligent illumination control and energy-saving management, and provides an illumination state monitoring management method and system for energy-saving operation of a subway station, and the method comprises the steps: continuously collecting the electrical characteristics, optical performance parameters, equipment basic attributes and historical operation records of illumination nodes, and carrying out the fusion to form analysis basic data; identifying potential fault risk nodes based on the data; simulating a fault influence by using a digital twin model and comparing the fault influence with a safety standard; and starting preventive optical compensation or compensation-combined graded early warning according to a comparison result. The system correspondingly comprises a parameter acquisition module, a risk analysis module, an influence analysis module and an optical compensation and early warning module. According to the invention, fault advanced pre-judgment, accurate compensation and efficient operation and maintenance are realized, the energy-saving and safe operation requirements are balanced, and the intelligent management level of the illumination system is improved.

The invention is suitable for the technical field of wireless power transmission, and provides an electromagnetic shielding structure robust optimization method for a wireless power transmission system, which comprises the following steps: constructing a WPT system; an electromagnetic shielding structure is designed, energy transmission efficiency is improved, and an electromagnetic field in a non-working area is weakened; the method comprises the following steps: establishing a K-Trans proxy model, integrating uncertainty factors and shielding structure design parameters of a WPT system, and carrying out modeling on data by utilizing an improved Transform model and combining a Kolmogorov-Arnold representation theorem; and carrying out multi-target robust optimization based on a K-Trans proxy model by applying an MOEDO algorithm, generating a Pareto optimal solution set, and balancing the energy transmission efficiency and the electromagnetic shielding performance. The electromagnetic shielding structure is provided, the K-Trans proxy model and the MOEDO algorithm are used for optimization design, the problem of WPT system coupling mechanism offset is solved, and a new thought is provided for electromagnetic shielding and safety protection.

The invention discloses an optimization method and system for processing energy consumption of an intelligent machine tool, and belongs to the technical field of processing equipment control, and the method comprises the steps: obtaining operation data of the current intelligent machine tool during operation and material data on a conveying line, building a state switching demand analysis model, and generating a state switching demand index; according to the state switching demand index, whether the intelligent machine tool needs to operate at the lowest power or not is judged, and the operation state of the intelligent machine tool is adjusted to operate at the lowest power through the control end; according to the material fault end position, the material arrival prediction time is generated, a machine tool starting opportunity analysis model is established, the intelligent machine tool starting time is generated, and the intelligent machine tool is started through the control end; according to the method, precise shutdown decision and start-stop opportunity optimization can be realized, invalid idle energy consumption and frequent start-stop loss can be reduced, energy consumption saving and equipment service life maintenance are balanced, and the energy utilization efficiency is effectively improved on the premise that the machining efficiency is guaranteed.

The invention relates to the technical field of holographic electric quantity sensing and local hot spot regulation and control, in particular to an intelligent control system and method for energy-saving turn-off of an air conditioner based on holographic electric quantity sensing. The position marking unit associates the equipment position with an air conditioner airflow path, records a hot spot area wind speed reference value and an attenuation coefficient and marks a hot spot influence range, and the control unit calculates the minimum wind speed of a hot spot for maintaining a standard temperature through a heat diffusion model, predicts a global heat load in combination with the total electric quantity, coordinates frequency reduction of a compressor and generates a wind speed instruction. The fan control unit adjusts the wind speed in a partitioned mode, self-adaptive compensation is started in combination with actually-measured temperature rise, bidirectional closed-loop control over the fan and the compressor is achieved, and the energy-saving and temperature-control requirements are balanced.

The invention relates to the technical field of communication energy saving, in particular to a wireless communication equipment energy saving system and method.The wireless communication equipment energy saving system comprises a data sensing module, a risk prediction module, an energy saving optimization module, an energy saving strategy decision module and an execution management module, and the data sensing module is used for collecting equipment information; the risk prediction module is used for constructing a risk prediction model, calculating risk probability distribution and dividing risk levels according to the risk probability distribution; the energy-saving optimization module is used for constructing a time period feature analysis engine and an energy-saving adjustment optimization model and generating an optimal decision variable; the energy-saving strategy decision module is used for constructing a strategy cooperation engine and obtaining a target energy-saving strategy according to the optimal decision variable and the risk level; and the execution management module is used for generating and executing an energy-saving instruction, managing dormancy and awakening of the equipment and monitoring a strategy execution effect. Therefore, the problems of fixed strategy, lack of dynamic adaptability, incapability of balancing energy consumption and communication quality and the like in the existing energy-saving technology are solved.

The invention discloses a material warehouse management system based on path collaborative planning, and relates to the field of material warehouse management, the system comprises the following components: a data acquisition module, a data processing module, a path planning module and an equipment control module; according to the method, a multi-objective function containing equipment energy consumption parameters and operation time is constructed, an improved dynamic weight Pareto evolutionary algorithm is adopted for solving, the two objectives of energy consumption and operation time can be dynamically balanced, an energy consumption-efficiency coupling coefficient is introduced in the algorithm iteration process, and the energy consumption and efficiency of the equipment can be effectively improved. The optimization degree is adjusted in real time according to the optimal solution of the current solution set, the situation that the performance of another target is greatly reduced due to excessive pursuit of a single target is avoided, the comprehensive benefit of path planning is remarkably improved through the intelligent balance mechanism, and the system can keep an efficient and energy-saving operation state in different operation scenes.

The present invention discloses a control method and system for an energy-saving ground-source heat pump, comprising: establishing a dynamic model of a ground-source heat pump system including an indoor heat balance, a ground-source heat pump unit, and a soil heat exchange model; obtaining its topological network through coupling; designing a distributed control and fault-tolerant operation strategy based on the topological network structure; locally controlling each node based on its location and information about adjacent nodes; constructing a state-space model; finding an optimal control action sequence through quadratic programming to balance energy consumption with an objective function of indoor and outdoor temperature deviation to achieve an optimal operating state; learning the mapping relationship between the optimal operating state and environmental parameters through a neural network; designing a ground-source circulation flow control algorithm to achieve automatic adjustment of the circulation pump flow distribution and the unit operating parameters. This method can effectively improve the control accuracy and stability of the ground-source heat pump system, ensure its reliable operation under complex working conditions, significantly improve energy utilization efficiency, achieve energy conservation and consumption reduction, and have good interpretability.

This application relates to a control method, apparatus, and television device. The method includes: obtaining the current electricity price period based on peak-valley tiered electricity price data for the user's region, and obtaining the user's household electricity consumption data; determining whether preset energy-saving conditions are met based on the current electricity price period and household electricity consumption data; when the preset energy-saving conditions are met, generating an adjustment strategy based on the preset energy-saving conditions and the television device's equipment parameter data; and controlling the television device to execute the adjustment strategy, so that the television device can reduce power consumption while maintaining continuous playback of media content. Using this application, intelligent energy-saving control linked to peak-valley tiered electricity pricing can be achieved, balancing energy saving of the television device with the viewing experience.

The invention provides a communication method and related equipment, and relates to the technical field of wireless communication. The method comprises the steps that the intelligent surface determines a first panel pattern of the intelligent surface and a weight value of each electromagnetic unit group in the first panel pattern according to first indication information configured by network equipment, the first panel pattern represents a grouping mode of a plurality of electromagnetic units, and each electromagnetic unit group comprises at least one electromagnetic unit; and controlling each electromagnetic unit group based on the first panel pattern and the weight value of each electromagnetic unit group in the first panel pattern, so as to forward the data from the sending end to the receiving end through the intelligent surface, thereby reducing independent control instructions for a large number of electromagnetic units, reducing the complexity and transmission delay of a communication system, and improving the communication efficiency. Energy efficiency and performance are balanced, and high throughput, low time delay and high energy efficiency of a communication system are realized.

The invention discloses a lightweight model deployment method of an AI edge computing terminal and a low-power-consumption processing device, and relates to the technical field of artificial intelligence and edge computing, and the method comprises the steps: collecting the total energy consumption of the terminal and the power consumption data of a processor, a memory and a communication module in real time; by acquiring the energy consumption data of the terminal and the hardware in real time and establishing dynamic association of energy consumption and model adjustment, accurate matching of lightweight model deployment and an energy consumption state is realized, the problem of disjunction of model deployment and power consumption control is solved, sub-models are dynamically switched or calculation precision is reduced when the energy consumption exceeds a threshold value, and the energy consumption is reduced. When the energy consumption is too high, the complexity of the model is reduced in time, the balance between the energy consumption and the reasoning performance is realized, the problem that the energy consumption continuously rises or the performance is suddenly reduced is avoided, the cooperation of task execution and energy consumption management is realized by adjusting the task execution frequency and priority and combining closed-loop feedback continuous optimization, the reasoning performance is ensured, meanwhile, the consumption is accurately controlled, and the efficiency is improved. And the stability and the practicability in a complex environment are improved.

The invention provides an unmanned aerial vehicle alternate relay communication and trajectory optimization and power distribution method and system, and relates to the technical field of unmanned aerial vehicles, comprising the steps of establishing and managing an unmanned aerial vehicle communication network, realizing data transmission and reception among a source node, a target point and an unmanned aerial vehicle relay node, and optimizing the transmitted data, setting a flight path and a power distribution strategy of the unmanned aerial vehicle according to the transmitted data, making the power distribution strategy by taking maximization of the energy efficiency of the unmanned aerial vehicle in the flight process as a target, balancing the energy efficiency and communication quality, and monitoring and adjusting the flight path and the power distribution strategy of the unmanned aerial vehicle in real time to obtain state information of the unmanned aerial vehicle. And adjusting the transmitting power of the unmanned aerial vehicle according to the state information of the unmanned aerial vehicle, and controlling the unmanned aerial vehicle. According to the method, the unmanned aerial vehicle communication network is established and managed, and data transmission, flight path and power distribution are optimized in real time, so that the energy efficiency, communication quality, flexibility and task success rate of the unmanned aerial vehicle system can be remarkably improved.

The invention relates to the technical field of intelligent locks, in particular to an intelligent lock with an intelligent acquisition function and a control method thereof.Importance levels of corresponding acquisition functions are represented through attribute weights, then the attribute weights are corrected through data calling records, and personalized weights better conforming to user habits are obtained; then a fitness function is determined based on the personalized weight, so that an optimal acquisition function calling strategy can be found through an optimization algorithm, and the calling strategy not only can select and reject a plurality of acquisition functions according to the residual electric quantity so as to prolong standby time, but also can match user habits and reserve common and important acquisition functions of a user; the purpose of balancing energy consumption and functions of the intelligent lock is perfectly achieved, it is ensured that safety and convenience are provided, high efficiency and energy efficiency are kept, user experience is greatly improved, and good prospects are achieved.

The invention relates to the technical field of equipment energy-saving control, in particular to a power distribution switch control equipment energy-saving optimization method and system based on data fusion, and the method comprises the steps: importing control record data and equipment parameter data of control equipment into an equipment control difficulty degree analysis model, and analyzing the control difficulty degree of the control equipment; importing the switch operation data and the current operation state data of the power distribution switch into an operation stability analysis model, and analyzing the operation stability of the power distribution switch; constructing a control equipment energy-saving benefit evaluation model, importing the control difficulty degree analysis result of the control equipment and the operation stability analysis result of the power distribution switch into the control equipment energy-saving benefit evaluation model, and evaluating the energy-saving benefit of the control equipment; and adjusting the energy-saving mode according to an energy-saving benefit evaluation result of the control equipment. Energy-saving mode parameters can be accurately and dynamically optimized, energy saving and equipment operation are balanced, and the adaptability and the energy-saving effect of the energy-saving mode are improved.

The invention relates to the field of ship energy control, in particular to an electric ship energy control method based on working condition recognition. The method comprises the following steps: acquiring planned route information, and analyzing historical working conditions of route segments one by one to obtain historical working condition characteristics; real-time working condition parameters in the ship navigation process are collected; positioning and matching a plurality of sub-legs according to the real-time working condition parameters, and constructing a sub-leg working condition feature set; working condition deviation comparison is carried out on the historical working condition features according to the sub-leg working condition feature set, and a deviation state sequence is determined; performing propulsion power gap calculation based on the deviation state sequence to obtain a power gap compensation value; battery capacity information is identified, current endurance state evaluation is carried out, and an endurance evaluation value is obtained; and carrying out endurance constraint correction on the power gap compensation value according to the endurance evaluation value to obtain a power constraint adjustment value. According to the invention, through real-time working condition identification and analysis, energy efficiency optimization, endurance safety and operation reliability are considered under complex navigation working conditions.

The present application relates to the technical field of agricultural Internet of Things and environmental intelligent control, and particularly relates to a greenhouse environment self-adaptive regulation and control system based on artificial intelligence, comprising: an environment acquisition module, which is used for acquiring multi-dimensional environment data in real time through distributed multi-source sensors; a central controller, which is used for generating an optimized regulation and control strategy; a regulation and control execution module, which is used for driving an execution device to adjust; the central controller comprises a multi-source data fusion unit, an AI decision unit and a dynamic optimization engine, which are respectively responsible for data filtering and fusion, generating an initial regulation and control strategy based on a space-time joint AI model, and reconstructing and optimizing the initial regulation and control strategy through a multi-objective optimization algorithm. The present application improves response real-time performance through multi-source sensing and data fusion, realizes predictive regulation and multi-parameter coordination by using an AI model, balances energy consumption, growth and carbon emission by combining multi-objective optimization, and supports long-term self-adaptation and strategy iteration of the system.

The invention relates to the technical field of data center management, in particular to an intelligent optimization control system for data center energy management, which realizes cross-domain dynamic linkage by constructing energy, network and business three-side collaborative twinbodies, balances energy and computing power resources while guaranteeing business service levels, avoids global loss of local optimization, and improves the service quality. By using the twinborn rehearsal technology, the system can simulate the whole-process influence of different optimization strategies in a virtual space, and through a cooperative fault processing mechanism of a service and network side twinborn body, the system constructs a'fault early warning-load transfer-energy consumption compensation 'closed loop, thereby greatly reducing the risk of core service interruption, and improving the reliability of the system. The system toughness and the stable operation capability of optimization control in an extreme scene are enhanced, a contribution degree, reputation and benefit evaluation method is provided, an abstract optimization effect is converted into a comparable numerical system, an objective and explainable decision basis is provided for selection of an optimization control strategy, and subjective deviation driven by experience is avoided.

A cluster-based adaptive routing method and system for virtual power plant wireless terminals, relating to the technical field of virtual power plants. A plurality of terminal nodes collect energy and transmit the energy to a base station, and the remaining energy of each terminal node during the energy transmission is calculated. The probability that each terminal node is selected as a cluster head node is calculated on the basis of the remaining energy of each terminal node, and the terminal nodes as the cluster head nodes are determined on the basis of the probabilities. A message is broadcast to all ordinary nodes by the cluster head nodes. Clustering is performed by comparing the signal strengths of messages received by the ordinary nodes from the respective cluster head nodes. The distance between each cluster head node and the base station and the distance between the cluster head nodes are used as criteria to determine a preset transmission mode having the lowest energy consumption for each cluster head node, thereby adaptively selecting an optimal transmission mode for multi-mode transmission to the base station to reduce and balance energy consumption of each data collection node terminal in the virtual power plant.

The invention discloses a wireless energy information cooperative transmission method and system based on polarization modulation, the system is composed of a transmitting end and a receiving end, the transmitting end comprises a radio frequency power source, a radio frequency switch and a transmitting antenna; the receiving end comprises a receiving antenna, two rectifying circuits, a voltage comparator, an information decoding module and an energy management module. The radio frequency switch is integrated with the transmitting antenna, and the receiving antenna is integrated with the rectifying circuit, so that the size is effectively reduced; a frequency mixer and a local oscillator required in a traditional demodulation circuit can be omitted at the receiving end, and energy consumed by information demodulation is reduced. Meanwhile, a battery is not needed, energy is only provided by a radio frequency signal output in the transmitting end, and the energy is collected and boosted through the energy management module to supply power to equipment; according to the method, energy and information transmission do not need to be balanced, high-speed information transmission can be realized on the premise of keeping high energy conversion efficiency, and the robustness is high.

The present invention discloses a method and system for optimizing the processing energy consumption of intelligent machine tools, which belongs to the field of processing equipment control technology. The method comprises obtaining the operating data of the current intelligent machine tool and the material data on the conveyor line, establishing a state switching demand analysis model, and generating a state switching demand index; judging whether the intelligent machine tool needs to operate at the lowest power according to the state switching demand index, and adjusting the operating state of the intelligent machine tool to the lowest power operation through the control end; generating a material arrival prediction time according to the end position of the material fault, and then establishing a machine tool start-up timing analysis model, generating the intelligent machine tool start-up time, and starting the intelligent machine tool through the control end; the present invention can realize accurate shutdown decision-making and start-stop timing optimization, and can also reduce invalid idling energy consumption and frequent start-stop loss, balance energy saving and equipment life maintenance, and effectively improve energy utilization efficiency while ensuring processing efficiency.

The invention provides an energy recovery and conversion method and system for an automobile brake power device, and relates to the technical field of energy recovery and conversion. Vehicle brake state collection is carried out through a sensor network, brake state collection data are obtained, and vehicle brake state analysis and judgment are carried out according to the brake state collection data; performing energy recovery potential analysis according to the vehicle braking state analysis and judgment information to obtain energy recovery potential analysis data, and performing energy recovery state analysis and judgment according to the energy recovery potential analysis data; and performing energy conversion recovery control analysis according to the energy recovery state analysis judgment information to obtain energy conversion recovery control data, and performing control state analysis judgment according to the energy conversion recovery control data to obtain energy conversion recovery control judgment information. Energy recovery efficiency and braking safety are both considered, device loss is reduced, and the service life of equipment is prolonged.

The present invention discloses an internal loop balancing control method suitable for a modular energy storage system. The control method implements balancing based on the DC part of the energy storage system composed of multiple half-bridge converter sub-modules connected in series. By leveraging the characteristic that the DC bus voltage of the energy storage system can be arbitrarily adjusted when idle, the balancing energy is alternately transferred between the battery group to be discharged and the DC bus capacitor, and between the DC bus capacitor and the battery group to be charged, thereby achieving indirect balancing between the battery group to be discharged and the battery group to be charged. The balancing method proposed in the present invention can also be used in other modular energy storage systems, and balancing can be achieved without the help of additional balancing circuit hardware.

This application relates to the field of 5G communication technology, and provides a 5G terminal power consumption optimization method, computer equipment, and medium. The method includes: acquiring the service traffic characteristics and temperature information of the 5G terminal, identifying the current service scenario type of the terminal, retrieving a matching target strategy to dynamically adjust the discontinuous reception parameters of the communication module, and then comprehensively determining the sleep level based on the adjusted discontinuous reception parameters, service scenario type, and temperature information; performing coordinated sleep control on the communication module and the main control processor; and simultaneously reporting the operating status data and local power management parameters to the cloud platform, receiving and executing updated parameters sent from the cloud to form a closed-loop optimization. Without affecting the real-time performance of control services and the reporting success rate of data acquisition services, this method achieves a significant reduction in the overall power consumption of the 5G terminal, effectively solving the technical problem of balancing energy saving and service performance in existing fixed-parameter solutions.

A method implemented by an energy management system (EMS) to optimize energy distribution in an extreme fast-charging (XFC) system includes (1) generating temporal maps for each of a plurality of energy sources, including projected capacity and energy cost over time, (2) generating a temporal map of projected load of one or more EV chargers within the XFC system, and (3) selecting one or more of the energy sources to supply energy to the XFC system over a predetermined time period based on cost, availability, and demand forecasts. This selection, for example, dynamically balances energy costs, ensures charging reliability, and / or optimizes the XFC system to support high-power charging with minimal operational expenses.

The invention relates to the technical field of crossing of mechanical engineering and process control, discloses an airflow spray dryer energy efficiency energy-saving and efficiency-improving method and system based on big data, and aims to solve the problems that atomization parameters are rigid, a nozzle is easy to block, control lags and energy efficiency and quality are difficult to consider in the drying process of high-viscosity slurry. The method comprises the following steps: acquiring slurry viscosity and droplet particle size distribution through high-frequency online rheological sensing and high-speed imaging; multi-source time sequence data are fused and input into a lightweight spatial-temporal feature extraction network, and optimization instructions of the fan rotating speed, the nozzle aperture and the hot air temperature are output in a millisecond level; and the piezoelectric fine adjustment mechanism and the frequency conversion fan are driven to execute self-adaptive regulation and control, and preventive maintenance is achieved in combination with micro-vibration anti-blocking and blocking risk prediction. The system integrates a sensing module, a modeling module, an execution module and an optimization module, the heat energy utilization rate is remarkably increased, and the diameter deviation of liquid drops is controlled within a small range.

The invention belongs to the related technical field of Internet of Things communication, and discloses a dual-mode communication node data access method and system based on an unmanned aerial vehicle, and the method comprises the steps: carrying out the topological block division; accessing each block in sequence; for each block, a wake-up frame is broadcasted through a first communication module to determine a to-be-planned node of the block, an internal path optimization model of the block is constructed, and the energy constraint of the unmanned aerial vehicle is that the energy consumption of the unmanned aerial vehicle for completing block access does not exceed the energy consumption upper limit; the working mode constraint is that the unmanned aerial vehicle vertically descends to a hovering point just above the node and performs data collection through the second communication module during hovering at the hovering point; the optimization target comprises the shortest access time in the block; and solving the model to obtain an access strategy in the block. On the basis of the method, energy consumption and transmission rate can be taken into account when a data recovery task is oriented to large-scale nodes, the overall planning difficulty is reduced, the node access dynamic adaptability is improved, and high-efficiency and high-reliability data recovery is realized.